modeling_alphapilot.py

import torch
import torch.nn as nn
from transformers import PreTrainedModel
from .configuration_alphapilot import AlphaPilotConfig

class AlphaPilotModel(PreTrainedModel):
    config_class = AlphaPilotConfig

    def __init__(self, config):
        super().__init__(config)
        
        layers = []
        input_dim = config.state_dim
        
        for h_dim in config.hidden_layers:
            layers.append(nn.Linear(input_dim, h_dim))
            layers.append(nn.ReLU())
            input_dim = h_dim
            
        layers.append(nn.Linear(input_dim, config.action_dim))
        
        self.net = nn.Sequential(*layers)

    def forward(self, x):
        return self.net(x)